Jonathan Mugan

I am a computer science researcher specializing in machine learning and AI.
I completed a postdoc at Carnegie Mellon University,
and I received a PhD in Computer Science from the University of Texas at Austin.

DeepGrammar,
A Web Application

Grammar checking using deep learning and deep symbolic processing

We all make mistakes when we write, and it would be nice if a computer could help us see the ones that spell checkers miss.
Grammar checking is hard because language is squishy, making it difficult to simply write down the rules and check that they are followed.
This lack of regularity is why grammar checkers have always been so poor. Fortunately, a relatively new technique in machine learning called
deep learning allows computers to be as squishy as our language, and effective grammar checking is finally possible.

Happy Cyborg,
A Web Application

Upload your personality to the cloud as a Twitter cyborg.

Happy Cyborg is a web application that learns your personality and acts as you would on Twitter.
It starts conversations, follows people based on your interests, and filters tweets to find the ones that you would enjoy reading.

Research,
Artificial Intelligence and Machine Learning

My research focuses on the goal of making the squishy reality of our everyday world available to computation.

My PhD thesis focused on the question of how a robot can acquire knowledge through autonomous exploration.
As a postdoc at Carnegie Mellon University, I explored how computers can use both context and feedback to
learn the privacy preferences of users of mobile devices. My current research is in natural language processing and deep learning.